SWUTC Research Project Description
Effect of Aggregate Micro- and Macro-texture on Pavement Skid Resistance
University: University of Texas at Austin
Principal Investigator:
Jorge Prozzi
Department of Civil and Environmental Engineering
(512) 471-4771
Project Monitor:
Feng Hong
Pavement Specialist
TxDOT
Austin, TX 78731
Funding Source: USDOT and State of Texas General Revenue Funds
Total Project Cost: $75,900
Project Number: 600451-00085
Date Started: 1/1/13
Estimated Completion Date: 12/31/13
Project Summary
Project Abstract:
The skid resistance of the surface of the highway is controlled by its micro-texture and macro-texture. However, it is not clear under which conditions the contributions of micro- and macro-textures are dominant and what specific frequencies are important. In this study, we will study the contribution of both surface properties to skid resistance under dry and wet conditions and under different speeds. The study will aim at quantifying their effects on skid and to develop recommendations to increase surface skid and, therefore, to improve highway safety and reduce the number of total highway accidents. During this study we will address two primary objectives: 1) we will define a methodology for characterizing micro- and macro-texture from 3D scan of pavement surface; and 2) we will model skid resistance assessing separate effect of micro and macro-texture. The first objective will be addressed by collecting very high-definition image data on pavement materials and pavement surfaces. This information will be analyzed by Fourier Transform (or other equivalent methodology) to develop the model that will quantify the effect of micro- and macro-texture on skid resistance and, therefore, on highway safety.
Project Objectives:
During this study we will address two primary objectives: 1) Define method for characterizing micro-texture from 3D scan of pavement surface; and 2) Model skid resistance assessing separate effect of micro and macro texture. The first objective will be addressed by collecting very high-definition image data on pavement materials and pavement surfaces. This information will be analyzed by Fourier Transform (or other equivalent methodology) to develop the model that will quantify the effect of micro- and macro-texture on skid resistance and, therefore, on highway safety.
Task Descriptions:
Task 1: Literature Review
An extensive literature review will be conducted not only nationally but also internationally. In this area, the leading research is taking place in Australia, France, New Zealand and the United Kingdom. However, research efforts in other countries and in the United States will also be reviewed. The search will focus on previous studies that have attempted to assign the effect of micro- and macro-texture to different aspects of the skid resistance of the pavement surface. In addition, research studies on wave and frequency analysis will be reviewed to determine the most robust manner to extract dominant frequencies out of a spectrum and to relate them to specific aspect of surface skid.
Task 2: Experimental Design
It is know that skid resistance is not a unique property of the pavement surface but, for a given pavement varies, inter-alia, with speed and pavement condition (dry o wet). In Texas, many pavement surfaces are common, including a variety of surface treatments, hot-mix asphalt of different gradations, concrete pavements, etc. Thus, during this task we will evaluate the main variables that control skid and develop an experiment that accounts at least for the following:
- Surface condition: wet and dry
- Surface type: seal coat, dense mixture, porous friction courses (PFC), and continuously reinforced concrete pavements (CRCP).
- Material microtexture: this is controlled by material type so hard and soft crushed limestone and siliceous river gravel will be considered.
- Speed: when possible three different speeds will be simulated.
Task 3: Data Collection and Analysis
The following texture data will be collected: 1) Sand Patch Method; 2) Circular Track Meter (CTM); 3) TxDOT 3-D Texture Scanner; and 4) AMES Laser Texture Scanner (this device will be purchase for this project as it is the only device available capable of characterizing the highest frequency/lower amplitude range, i.e. < 0.5 mm). In terms of skid resistance, depending on availability and site conditions, the following equipment will be used: 1) Skid with TxDOT Skid Trailer; 2) British Pendulum Test (BPT), and 3) Dynamic Friction Tester (DFT).
In the spatial domain the following statistics will be calculated: mean profile depth (MPD), slope variance (SV) and root mean square (RMS). In the frequency domain, some of the statistics of interest include the waviness as measured by the slope of the logarithm transformation of the power spectral density and the intercept of this transformation. This statistics will be correlated with measurements of skid resistance at different speed on different surfaces and under different conditions.
Task 4: Development of Recommendations
The analysis conducted as part of Task 3 will reveal which frequency contents (which portions of micro or macro) control skid resistance under the various conditions analyzed. Therefore, during this task, the findings of the analysis will be summarized and a series of recommendations will be prepare that will enable the designer to select the optimum combination of material and surface type under the prevailing environmental conditions so as to maximize safety and minimize the total number of accidents at a given location.
Task 5: Technology Transfer and Reporting
The objectives of this task are to deliver a report documenting the research performed and to disseminate the main results of the study by submitting a paper for presentation at the next Annual Meeting of the Transportation Research Board and a prestigious relevant international transportation conference to be determined.
Implementation of Research Outcomes:
This study explored different ways to characterize the micro-texture of pavement surfaces with the main objective of quantifying the effect of accounting for both the micro and the macro components of the texture, rather than just the macro-texture, on the prediction of skid resistance.
Products developed by this research:
Presentation: Effect of Aggregate Micro- and Macro-texture on Pavement Skid Resistance, Prasad Buddhavarapu, University of Texas at Austin, presented to the Southern African Transportation Conference, Pretoria, South Africa, July 2015.
Impacts/Benefits of Implementation:
The authors conclude that accounting for both the macro- and the micro-texture components of the surface will significantly enhance the prediction of British Pendulum Number (BPN) of flexible pavements as oppose to accounting solely for the macro-texture component. Such improvement will allow transportation agencies to better manage skid resistance and therefore to improve road safety.
Web Links:
Final Technical Report